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All Journal Journal of Data Mining and Information Systems
Rexa, Nafa
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Computer Science & IT

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Implementasi Market Basket Analysis Dengan Algoritma Frequent Pattern Growth Pada Data Transaksional di Electronic Commerce Fairuzindah, Athaya; Islami, Istiqomah Rabithah Alam; Rexa, Nafa; Anggraini, Silvia; Sunandi, Etis
JDMIS: Journal of Data Mining and Information Systems Vol. 3 No. 2 (2025): August 2025
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/jdmis.v3i2.4593

Abstract

The Growth of the e-commerce industry has resulted in a massive volume of transaction data, necessitating effective data analysis techniques to extract customer purchasing patterns. The Frequent Pattern Growth (FP-Growth) algorithm is one of the data mining methods that can be used to identify frequently occurring purchase patterns without explicitly generating candidate itemsets. This study aims to implement and evaluate the performance of the FP-Growth algorithm in analyzing e-commerce transaction data to identify recurring shopping patterns. The research methodology includes transaction data collection, data preprocessing, FP-Growth algorithm implementation, and result analysis. This study utilizes an e-commerce transaction dataset from an online retail store based in the United Kingdom, comprising 541,909 transaction records. The research findings indicate that the FP-Growth algorithm is efficient in identifying frequently occurring transaction patterns. Using a support threshold of 1% and a confidence level of 80%, 13 association rules were discovered, demonstrating relationships between frequently co-purchased products. Further analysis shows that these findings can be leveraged by e-commerce businesses to develop marketing strategies based on product recommendations. In conclusion, the FP-Growth algorithm is an effective approach for extracting purchasing patterns from large-scale e-commerce transaction data.
Co-Authors Anggraini, Silvia Fairuzindah, Athaya Islami, Istiqomah Rabithah Alam Sunandi, Etis